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<span class="breadcrumb-node">Avg Aggregation</span>
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<div class="section">
<div class="titlepage"><div><div>
<h2 class="title">
<a id="search-aggregations-metrics-avg-aggregation"></a>Avg Aggregation<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/aggregations/metrics/avg-aggregation.asciidoc">edit</a>
</h2>
</div></div></div>
<p>A <code class="literal">single-value</code> metrics aggregation that computes the average of numeric values that are extracted from the aggregated documents. These values can be extracted either from specific numeric fields in the documents, or be generated by a provided script.</p>
<p>Assuming the data consists of documents representing exams grades (between 0
and 100) of students we can average their scores with:</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">POST /exams/_search?size=0
{
    "aggs" : {
        "avg_grade" : { "avg" : { "field" : "grade" } }
    }
}</pre>
</div>
<div class="console_widget" data-snippet="snippets/320.console"></div>
<p>The above aggregation computes the average grade over all documents. The aggregation type is <code class="literal">avg</code> and the <code class="literal">field</code> setting defines the numeric field of the documents the average will be computed on. The above will return the following:</p>
<div class="pre_wrapper lang-console-result">
<pre class="programlisting prettyprint lang-console-result">{
    ...
    "aggregations": {
        "avg_grade": {
            "value": 75.0
        }
    }
}</pre>
</div>
<p>The name of the aggregation (<code class="literal">avg_grade</code> above) also serves as the key by which the aggregation result can be retrieved from the returned response.</p>
<div class="section">
<div class="titlepage"><div><div>
<h3 class="title">
<a id="_script"></a>Script<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/aggregations/metrics/avg-aggregation.asciidoc">edit</a>
</h3>
</div></div></div>
<p>Computing the average grade based on a script:</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">POST /exams/_search?size=0
{
    "aggs" : {
        "avg_grade" : {
            "avg" : {
                "script" : {
                    "source" : "doc.grade.value"
                }
            }
        }
    }
}</pre>
</div>
<div class="console_widget" data-snippet="snippets/321.console"></div>
<p>This will interpret the <code class="literal">script</code> parameter as an <code class="literal">inline</code> script with the <code class="literal">painless</code> script language and no script parameters. To use a stored script use the following syntax:</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">POST /exams/_search?size=0
{
    "aggs" : {
        "avg_grade" : {
            "avg" : {
                "script" : {
                    "id": "my_script",
                    "params": {
                        "field": "grade"
                    }
                }
            }
        }
    }
}</pre>
</div>
<div class="console_widget" data-snippet="snippets/322.console"></div>
<div class="section">
<div class="titlepage"><div><div>
<h4 class="title">
<a id="_value_script"></a>Value Script<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/aggregations/metrics/avg-aggregation.asciidoc">edit</a>
</h4>
</div></div></div>
<p>It turned out that the exam was way above the level of the students and a grade correction needs to be applied. We can use value script to get the new average:</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">POST /exams/_search?size=0
{
    "aggs" : {
        "avg_corrected_grade" : {
            "avg" : {
                "field" : "grade",
                "script" : {
                    "lang": "painless",
                    "source": "_value * params.correction",
                    "params" : {
                        "correction" : 1.2
                    }
                }
            }
        }
    }
}</pre>
</div>
<div class="console_widget" data-snippet="snippets/323.console"></div>
</div>

</div>

<div class="section">
<div class="titlepage"><div><div>
<h3 class="title">
<a id="_missing_value"></a>Missing value<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/aggregations/metrics/avg-aggregation.asciidoc">edit</a>
</h3>
</div></div></div>
<p>The <code class="literal">missing</code> parameter defines how documents that are missing a value should be treated.
By default they will be ignored but it is also possible to treat them as if they
had a value.</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">POST /exams/_search?size=0
{
    "aggs" : {
        "grade_avg" : {
            "avg" : {
                "field" : "grade",
                "missing": 10 <a id="CO179-1"></a><i class="conum" data-value="1"></i>
            }
        }
    }
}</pre>
</div>
<div class="console_widget" data-snippet="snippets/324.console"></div>
<div class="calloutlist">
<table border="0" summary="Callout list">
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO179-1"><i class="conum" data-value="1"></i></a></p>
</td>
<td align="left" valign="top">
<p>Documents without a value in the <code class="literal">grade</code> field will fall into the same bucket as documents that have the value <code class="literal">10</code>.</p>
</td>
</tr>
</table>
</div>
</div>

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